code: def test_threshold_with_variables(df_na):
      # Each row must have 100% data avaiable for columns ['Marks']
      imputer = DropMissingData(threshold=1, variables=["Marks"])
      X = imputer.fit_transform(df_na)
      assert list(X.index) == [0, 1, 2, 4, 6, 7]
  
      # Each row must have 25% data avaiable for ['City', 'Studies', 'Age', 'Marks']
      imputer = DropMissingData(
          threshold=0.75, variables=["City", "Studies", "Age", "Marks"]
      )
      X = imputer.fit_transform(df_na)
      assert list(X.index) == [0, 1, 4, 5, 6, 7]
  
file_path: feature_engine/tests/test_imputation/test_drop_missing_data.py
imports: import pytest
  from feature_engine.imputation import DropMissingData
label_desc: Use image node_id 8 for calling a global function with example usage: test_threshold_with_variables(df_na) without return types